Menstrual cycle hormones and oral contraceptives: a multimethod systems physiology-based review of their impact on key aspects of female physiology
Bibliographic record
Abstract
Hormonal changes around ovulation divide the menstrual cycle (MC) into the follicular and luteal phases. In addition, oral contraceptives (OCs) have active (higher hormone) and placebo phases. Although there are some MC-based effects on various physiological outcomes, we found these differences relatively subtle and difficult to attribute to specific hormones, as estrogen and progesterone fluctuate rather than operating in a complete on/off pattern as observed in cellular or preclinical models often used to substantiate human data. A broad review reveals that the differences between the follicular and luteal phases and between OC active and placebo phases are not associated with marked differences in exercise performance and appear unlikely to influence muscular hypertrophy in response to resistance exercise training. A systematic review and meta-analysis of substrate oxidation between MC phases revealed no difference between phases in the relative carbohydrate and fat oxidation at rest and during acute aerobic exercise. Vascular differences between MC phases are also relatively small or nonexistent. Although OCs can vary in composition and androgenicity, we acknowledge that much more work remains to be done in this area; however, based on what little evidence is currently available, we do not find compelling support for the notion that OC use significantly influences exercise performance, substrate oxidation, or hypertrophy. It is important to note that the study of females requires better methodological control in many areas. Previous studies lacking such rigor have contributed to premature or incorrect conclusions regarding the effects of the MC and systemic hormones on outcomes. While we acknowledge that the evidence in certain research areas is limited, the consensus view is that the impact of the MC and OC use on various aspects of physiology is small or nonexistent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".